Why Did AI Concept Stocks Plummet? SpaceX Falls Below $2 Trillion Market Cap, SanDisk and Micron Drop Over 13%

June 23, 2026 (Eastern Time), the U.S. stock market experienced a fierce sell-off centered around AI concept stocks. The Nasdaq Composite fell 2.21%, and the Nasdaq 100 plunged 3.3%. The Philadelphia Semiconductor Index dropped 7.87% in a single day, marking its largest one-day decline since June 5. This sell-off was not an isolated event but the result of multiple structural pressures releasing during a three-year valuation expansion cycle in the AI industry.

How large and severe is the current wave of AI concept stock declines?

Chip stocks became the hardest hit in this sell-off. SanDisk (SNDK) plummeted over 13%, breaking below the $2,000 mark; Micron Technology (MU) fell 13.18%; ARM declined over 10%; Qualcomm and Western Digital dropped over 8%; TSMC and Intel fell over 6%; AMD declined over 5%.

As a benchmark for AI computing power, Nvidia (NVDA) closed down 4.15%, with its market cap falling below $5 trillion. Tesla dropped 5.79%. Among large tech stocks, only Microsoft rose 1.8 against the trend.

The scope of this sell-off extended far beyond U.S. stocks. During the Asian trading session on June 23, the Korea KOSPI index triggered a circuit breaker after an 8% plunge, closing down 9.99%. Samsung Electronics fell 12.31%, SK Hynix dropped 12.47%. The A-share AI computing industry chain collectively adjusted, and Hong Kong tech stocks also declined simultaneously. From Asia-Pacific to North America, global capital is visibly retreating from high-beta tech assets at an accelerating pace.

What has changed in the valuation logic behind SpaceX’s $600 billion three-day market cap evaporation?

SpaceX is the most symbolic case in this round of sell-off. This aerospace and AI company, which completed a record-breaking IPO on June 12, experienced a full cycle from frenzy to panic within just two weeks of listing.

In the first week, SpaceX’s stock price reached a high of $225. However, over the next three trading days, the price declined consecutively, with a total drop of about 23%, evaporating over $600 billion in market value. Notably, on June 22, the stock plunged 16.4%, losing about $400.8 billion in market cap — the second-largest single-day market value loss in U.S. corporate history. On June 23, SpaceX’s stock fell below $150, which was its IPO opening price.

One of the immediate triggers for this plunge was the company’s announcement of a $20 billion bond issuance plan. SpaceX aimed to raise funds through debt to support AI infrastructure expansion, but market interpretation was not positive — for a company that has yet to turn a profit and is expected to continue cash burn until 2029, large-scale borrowing for expansion heightened concerns over liquidity and debt repayment capacity.

More critically, there are supply-side concerns. Currently, only about 5% of SpaceX shares are in circulation, with the remaining 95% still locked. As the lock-up periods from August to September come due, insiders could sell up to about 44% of the total shares, potentially increasing the free float by roughly nine times. Against a backdrop of cooling demand momentum, this potential supply shock is fundamentally reshaping the valuation structure of this stock.

Does Nvidia’s market cap falling below $5 trillion signal that the AI hardware narrative has reached a turning point?

Nvidia’s decline is also highly indicative. As the biggest beneficiary of the past three years’ AI compute scarcity narrative, Nvidia’s market cap briefly returned to $5 trillion in April 2026. However, since June, its stock price has continued to face downward pressure.

This is not just a simple stock correction. Goldman Sachs strategists pointed out in a June 23 report that a growing structural divergence is emerging: large-scale cloud providers continue to increase capital expenditure commitments, yet their stock prices have underperformed the broader market; meanwhile, AI hardware stocks like Nvidia and TSMC had previously outperformed against the trend. This divergence itself signals a mispricing in the market.

Morgan Stanley portfolio manager Andrew Slimmon commented, “The decline is mainly concentrated in AI-beneficiary stocks. I don’t think these companies are overvalued, but the trading has become too crowded. AI has become a momentum-driven theme. When a market theme becomes overly crowded, sharp corrections like this tend to happen.”

How extensive has the debt expansion for AI infrastructure become?

To understand the deeper logic behind this sell-off, we must examine the financing structure behind AI infrastructure development.

According to Morgan Stanley’s "AI Debt Financing Tracking Report," as of the end of May 2026, global issuance of AI-related bonds reached $236 billion, a 357% increase from the same period in 2025. Morgan Stanley projects total AI debt issuance for the year will surpass $570 billion. In April alone, issuance exceeded $74 billion, with 85% of project financing structured for data center construction, primarily through high-yield debt.

The four major U.S. tech giants — Google, Amazon, Meta, and Microsoft — are expected to spend about $650 billion to $725 billion on capital expenditures in 2026. The combined capital expenditure of Amazon, Microsoft, Alphabet, and Meta could reach $50k. Global AI capital spending in 2026 may approach $800 billion.

Worse still, off-balance-sheet liabilities are a growing concern. Morgan Stanley estimates that long-term procurement commitments, totaling about $982 billion; over $800 billion in unexecuted lease contracts; and hundreds of billions in vendor financing arrangements collectively create an off-balance-sheet exposure of approximately $1.8 trillion. These liabilities, outside the balance sheet, are real and lock in future cash outflows.

The overall gross leverage ratio of large cloud companies has surged from 0.9x in Q3 2025 to the current 1.8x. Morgan Stanley forecasts that Amazon and Meta’s free cash flow in 2026 will approach zero or turn negative, making incremental financing almost entirely dependent on new debt issuance.

Why are crypto assets also under pressure during this AI sell-off?

The plunge in AI concept stocks is not isolated within the tech sector — crypto assets are also feeling the pressure.

As of June 24, 2026, according to Gate data, Bitcoin (BTC) was trading at $62,595, down 2.1% in 24 hours; Ethereum (ETH) was at $1,662, down 3.7%. Leverage longs are being liquidated on a large scale.

The correlation between Bitcoin and the Nasdaq remains around 0.45, above its 10-year average. This indicates that during systemic risk events, Bitcoin still struggles to decouple from tech stocks. The market generally links Bitcoin’s decline to risk appetite cooling — after the AI stocks retraced gains, capital’s attitude toward high-volatility assets has become more cautious.

A notable structural change is that some Bitcoin miners are shifting toward AI data center hosting businesses, holding long-term power purchase agreements. Investors are beginning to evaluate these companies based on AI infrastructure valuation logic, focusing on their power capacity, data center assets, and customer contracts. This means the crypto mining sector is being incorporated into the AI infrastructure narrative — when AI hardware stocks sell off, this transmission chain can also impact crypto assets.

What kind of pressure test is the AI industry chain undergoing, from compute leasing prices to corporate budget tightening?

Over the past three years, the AI industry has been running along a simple but powerful logic: the scarcer the compute, the more reasonable the capital expenditure; the larger the expenditure, the higher the valuation; the higher the valuation, the easier the financing. But this self-reinforcing cycle is being interrupted by multiple forces simultaneously.

On the upstream, spot prices and forward contract prices in the compute leasing market have diverged in an unusual way. In the midstream, previously cost-insensitive tech giants are beginning to tighten AI budgets. At a deeper level, physical world constraints like power supply and engineering capacity are becoming harder constraints than chip manufacturing.

Goldman Sachs strategists warn that the AI market is like a stretched rubber band — persistent neglect of negative signals will eventually reach a critical point. Once any major tech giant cuts AI spending first, the entire valuation logic of the AI sector could be fundamentally reshaped.

Dario Perkins of TS Lombard notes that such a scale of capital expenditure is extremely rare in tech history. Historically, the collapse of any tech bubble was not due to technology failure but because money ran out or investors lost patience.

How to understand the risk transmission chain from AI concept stocks to crypto assets?

This round of sell-off reveals a clear risk transmission path:

First, AI hardware stocks (Nvidia, chip manufacturers) face valuation pressure directly. Second, AI+ narrative stocks (SpaceX) suffer more severe corrections due to high leverage and low float. Third, global risk assets (including crypto) are under systemic pressure as risk appetite declines.

The deeper logic is that: about $750 billion annually in AI capital expenditure, combined with roughly $1.8 trillion in off-balance-sheet exposure and over $570 billion in annual debt issuance, forms a highly dependent and fragile financing structure. When the market questions whether AI commercialization can sustain such capital consumption, the entire financing chain’s vulnerability is exposed.

For crypto markets, this means Bitcoin’s narrative as “digital gold” as a safe haven remains unfulfilled during systemic risk events. In a liquidity-tightening, risk-averse environment, crypto assets tend to move in tandem with high-beta tech stocks rather than serving as independent safe havens.

Summary

From June 23 to 24, 2026, AI concept stocks experienced the most intense collective sell-off since the start of this AI boom. SpaceX’s market cap evaporated over $600 billion in three days; Nvidia fell 4.15%; SanDisk and Micron dropped over 13% — behind these figures lies a collective revaluation of the sustainability of AI infrastructure capital expenditure.

Annual AI capital spending of about $750 billion, over $570 billion in AI-related debt issuance, and approximately $1.8 trillion in off-balance-sheet exposure depict a highly dependent ecosystem on continuous financing. As compute leasing prices decline, tech giants tighten budgets, and leverage ratios climb, the ecosystem’s fragility begins to surface.

For crypto assets, the correlation of about 0.45 between Bitcoin and Nasdaq indicates it still struggles to fully detach from tech stock volatility. Whether the AI stock sell-off is over or just the beginning of a larger correction depends on whether AI commercialization can generate sufficient returns before capital consumption reaches a critical point. The market is shifting from the “compute scarcity” narrative to a new phase of “ROI validation.”

FAQ

Q1: What is the core reason behind this wave of AI concept stock declines?

The core reason is the market’s concentrated concern over the sustainability of massive capital expenditure in AI infrastructure. About $750 billion annually in capital spending, combined with over $570 billion in AI-related debt issuance and roughly $1.8 trillion in off-balance-sheet exposure, has led the market to question whether AI commercialization can support such a scale of capital consumption.

Q2: Why did SpaceX’s stock fall so sharply?

After its IPO, SpaceX’s stock surged excessively in the short term, then faced three pressures: liquidity concerns triggered by the $20 billion bond issuance plan, supply shock expectations from the upcoming lock-up expiration of 95% of shares, and the fundamental reality that the company is not profitable and is expected to continue losing money until 2029.

Q3: Why are crypto assets affected by the AI stock sell-off?

Bitcoin’s correlation with the Nasdaq remains around 0.45, above its 10-year average. During systemic risk events, crypto assets still struggle to decouple from tech stocks. Additionally, some Bitcoin miners are shifting toward AI data center hosting, with long-term power purchase agreements, leading to their valuation being increasingly linked to AI infrastructure logic.

Q4: How large is the scale of AI capital expenditure?

The four major U.S. tech giants — Google, Amazon, Meta, and Microsoft — are expected to spend about $650 billion to $725 billion on capital expenditures in 2026. Global AI capital spending may approach $800 billion. As of late May 2026, global issuance of AI-related bonds reached $236 billion, with projections exceeding $570 billion for the year.

Q5: Does the decline in AI concept stocks mean the AI bubble has burst?

It’s too early to say the AI bubble has burst, but the market is transitioning from a “compute scarcity” narrative to a “ROI validation” phase. Goldman Sachs strategists warn that if any major tech company cuts AI spending first, the entire valuation logic of the sector could be fundamentally reshaped. The current correction should be viewed as a market adjustment to overheated trading rather than a definitive end to AI’s long-term prospects.